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<p>Multi-modal, multiscale imaging is crucial for quantitative high-content spatial profiling. We present an integrated image processing pipeline for comprehensive tissue analysis that combines quantitative phase microscopy for tissue architecture mapping, hyper-plex fluorescence imaging for immune microenvironment profiling, and whole-slide histopathology. This approach enables detailed morphological mapping of tissue architecture and cell morphology, while simultaneously linking them to the functional states of individual cells across the entire slide. By analyzing tissue biopsies from patients with ulcerative colitis, we demonstrate the potential of this pipeline for quantitative spatial analysis of molecular markers related to mucosal healing. Open-source and compatible with conventional microscopy systems, this pipeline provides a powerful tool for research and clinical applications through its comprehensive integration of quantitative, high-content, and histological imaging modalities.</p>

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Multimodal whole slide image processing pipeline for quantitative mapping of tissue architecture and tissue microenvironment

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月10日

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  • Maomao Chen,
  • Hongqiang Ma,
  • Xuejiao Sun,
  • Marc Schwartz,
  • Randall E. Brand,
  • Jianquan Xu,
  • Dimitrios S. Gotsis,
  • Phuong Nguyen,
  • Beverley A. Moore,
  • Lori Snyder,
  • Rhonda M. Brand,
  • Yang Liu

摘要

Multi-modal, multiscale imaging is crucial for quantitative high-content spatial profiling. We present an integrated image processing pipeline for comprehensive tissue analysis that combines quantitative phase microscopy for tissue architecture mapping, hyper-plex fluorescence imaging for immune microenvironment profiling, and whole-slide histopathology. This approach enables detailed morphological mapping of tissue architecture and cell morphology, while simultaneously linking them to the functional states of individual cells across the entire slide. By analyzing tissue biopsies from patients with ulcerative colitis, we demonstrate the potential of this pipeline for quantitative spatial analysis of molecular markers related to mucosal healing. Open-source and compatible with conventional microscopy systems, this pipeline provides a powerful tool for research and clinical applications through its comprehensive integration of quantitative, high-content, and histological imaging modalities.